This work describes the synthesis of tetra amino Zinc(II)metallophthalocyanine (Zn(II)TAPc) the synthesized molecules were characterized by spectral analysis are FT-IR, UV-Visible, TGA, XRD and electrochemical characterization. The electrochemical oxidation of dopamine (DA), ascorbic acid (AA) and uric acid (UA) was studied on MWCNT-Zn(II)TAPc/GCE due to its excellent electron transferring ability than the bare glassy carbon electrode and Zn(II)TAPc/GCE since there is tuned the surface area of glassy carbon electrode decorated with multiwalled carbon nano tubes and Zn(II)Pc (MWCNT-Zn(II)TAPc). Therefore electrochemical sensing of micromoler concentration of dopamine, ascorbic acid and uric acid has done on MWCNT-Zn(II)TAPc/GCE the linear range of (CV 0.02 – 50 μmol L−1 ), lower detection limit of (CV 0.0066 μmol L−1 ) and sensitivity of (CV 56.03 μAμM−1 cm−2 ), similarly AA, UA are discussed in the below table. The fabricated sensor shows good electrocatalytic activity than the modified electrode with Zn(II)Pc alone towards oxidation of bio-molecule. The MWCNT-Zn(II)TAPc/GCE shows good repeatability, stability and aunty leaching properties. The MWCNT-Zn(II)TAPc/GCE is highly stable, sensitive and reproducible for the micromolar detection of DA, AA and UA.

The ptroject investigates a use case of robust anomaly detection applied to the scenario of a photovoltaic production factory—namely, Enel Green Power’s 3SUN solar cell production plant in Catania, Italy—by considering a Monte Carlo based pre-processing technique as a valid alternative to other typically used methods. In particular, the proposed method exhibits the following advantages: (i) Outlier replacement, by contrast with traditional methods which are limited to outlier detection only, and (ii) the preservation of temporal locality with respect to the training dataset. After pre-processing, the authors trained an anomaly detection model based on principal component analysis and defined a suitable key performance indicator for each sensor in the production line based on the model errors. In this way, by running the algorithm on unseen data streams, it is possible to isolate anomalous conditions by monitoring the above-mentioned indicators and virtually trigger an alarm when exceeding a reference threshold. The proposed approach was tested on both standard operating conditions and an anomalous scenario. With respect to the considered use case, it successfully anticipated a fault in the equipment with an advance of almost two weeks, but also demonstrated its robustness to false alarms during normal conditions.

The paper-based colorimetric assays have been widely reported in literature being cost-effective, not requiring additional components (i.e. pump) for microfluidic handling of the solution, and avoiding the sample treatment thanks to the filtering property of the paper. In the last decade, the electroanalysis has discovered the utility of using paper as electrode-active support, converging the reported advantages of paper with the features of electroanalysis such the high sensitivity, selectivity, and the capability to work in complex matrices (e.g. coloured samples).

I will present the research activity carried out in the last 5 years at Nanobiosensing Lab and SENSE4MED at the Department of Chemical Science and Technologies of Tor Vergata University aimed to develop sustainable and cost-effective (bio)sensors for application in environmental, agrifood, security, and biomedical fields.